# -*- coding: utf-8 -*-
# @Time    : 2017/12/10 23:06
# @Author  : David.Dong
# @Email   : dww102@gmail.com
# @Software: PyCharm Community Edition


import numpy as np


# 6-1
# Assistant function

def loadDataSet(filename):
    dataMat = []
    labelMat = []
    with open(filename) as fr:
        for line in fr.readlines():
            lineArr = line.strip().split('\t')
            dataMat.append([float(lineArr[0]), float(lineArr[1])])
            labelMat.append(float(lineArr[2]))
        return dataMat, labelMat


def selectJrand(i, m):
    j = i  # we want to select any J not equal to i
    while (j == i):
        j = int(np.random.uniform(0, m))
    return j


def clipAlpha(aj, H, L):
    if aj > H:
        aj = H
    if aj < L:
        aj = L
    return aj


# dataMatIn:    数据集
# classLavels： 类别标签
# C：           松弛变量
# toler：       容错率（tolerant rate）
# maxIter：     最大循环次数

def smoSimple(dataMatIn, classLabels, C, toler, maxIter):
    dataMatrix = np.mat(dataMatIn)
    labelMat = np.mat(classLabels).transpose()
    b = 0
    m, n = np.shape(dataMatrix)
    alphas = np.mat(np.zeros((m, 1)))
    iter = 0

    while (iter < maxIter):
        alphaPairsChanged = 0
        for i in range(m):
            fXi = float(np.multiply(alphas, labelMat).T * (dataMatrix * dataMatrix[i, :].T)) + b
            Ei = fXi - float(labelMat[i])  # if checks if an example violates KKT conditions
            if ((labelMat[i] * Ei < -toler) and (alphas[i] < C)) or ((labelMat[i] * Ei > toler) and (alphas[i] > 0)):
                j = selectJrand(i, m)
                fXj = float(np.multiply(alphas, labelMat).T * (dataMatrix * dataMatrix[j, :].T)) + b
                Ej = fXj - float(labelMat[j])
                alphaIold = alphas[i].copy()
                alphaJold = alphas[j].copy()
                if (labelMat[i] != labelMat[j]):
                    L = max(0, alphas[j] - alphas[i])
                    H = min(C, C + alphas[j] - alphas[i])
                else:
                    L = max(0, alphas[j] + alphas[i] - C)
                    H = min(C, alphas[j] + alphas[i])
                if L == H:
                    print("L==H")
                    continue
                eta = 2.0 * dataMatrix[i, :] * dataMatrix[j, :].T - dataMatrix[i, :] * dataMatrix[i, :].T - dataMatrix[j,:] * dataMatrix[j, :].T
                if eta >= 0:
                    print("eta>=0")
                    continue
                alphas[j] -= labelMat[j] * (Ei - Ej) / eta
                alphas[j] = clipAlpha(alphas[j], H, L)
                if (abs(alphas[j] - alphaJold) < 0.00001):
                    print("j not moving enough")
                    continue
                alphas[i] += labelMat[j] * labelMat[i] * (alphaJold - alphas[j])  # update i by the same amount as j
                # the update is in the oppostie direction
                b1 = b - Ei - labelMat[i] * (alphas[i] - alphaIold) * dataMatrix[i, :] * dataMatrix[i, :].T - labelMat[j] * (alphas[j] - alphaJold) * dataMatrix[i,:] * dataMatrix[j,:].T
                b2 = b - Ej - labelMat[i] * (alphas[i] - alphaIold) * dataMatrix[i, :] * dataMatrix[j, :].T - labelMat[j] * (alphas[j] - alphaJold) * dataMatrix[j,:] * dataMatrix[j,:].T
                if (0 < alphas[i]) and (C > alphas[i]):
                    b = b1
                elif (0 < alphas[j]) and (C > alphas[j]):
                    b = b2
                else:
                    b = (b1 + b2) / 2.0
                alphaPairsChanged += 1
                print("iter: %d, i: %d, pairs changed %d" % (iter, i, alphaPairsChanged))
        if (alphaPairsChanged == 0):
            iter += 1
        else:
            iter = 0
        print("iteration number: %d" % iter)
    return b, alphas
